Patient-specific computational fluid dynamics (CFD) modeling provides detailed hemodynamic parameter information for diagnosing coronary artery disease and heart dysfunction, though widespread clinical adoption is hampered by computational demands and imaging limitations.
The emergence of new cardiac diagnostics and therapeutics of the heart has given rise to the challenging field of virtual design and testing of technologies in a patient-specific environment. Given the recent advances in medical imaging, computational power and mathematical algorithms, patient-specific cardiac models can be produced from cardiac images faster, and more efficiently than ever before. The emergence of patient-specific computational fluid dynamics (CFD) has paved the way for the new field of computer-aided diagnostics. This article provides a review of CFD methods, challenges and opportunities in coronary and intra-cardiac flow simulations. It includes a review of market products and clinical trials. Key components of patient-specific CFD are covered briefly which include image segmentation, geometry reconstruction, mesh generation, fluid-structure interaction, and solver techniques.
Zhong et al. (Tue,) conducted a review in Coronary Artery Disease and Cardiac Dysfunction. Computational Fluid Dynamics (CFD) was evaluated. Patient-specific computational fluid dynamics (CFD) modeling provides detailed hemodynamic parameter information for diagnosing coronary artery disease and heart dysfunction, though widespread clinical adoption is hampered by computational demands and imaging limitations.
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